It is conventionally held that 70-80% of business data has a geographic component. With GPS-enabled smart phones, cameras, tablets and navigational devices, the production of geographically unique data is increasing.
Buildings are basic referential objects in society. Community functions, organizations, corporations, social status and many types of information production are frequently related to a building address. In the example of real estate, buildings and units of space within the building are the marketable product and vast amounts of data are generated to describe the characteristics of a property.
Despite the growth in geographically unique data and the referential utility of a building, a generic method does not exist for visualizing multi-media data in three-dimensional space relating specifically to a subject building.
Existing means of combining data and content of various media types (media types that are geographically unique, widely sourced from diverse contributors, time sensitive and frequently updated) generally combine each data element through multiple screens within a browser. This compartmentalization of the data does not integrate it in an informative manner with its location.
For example, the availability of real estate for sale or for lease is generally represented in two-dimensional formats: maps showing location in terms of longitude and latitude, visual media, such as photographs or videos of the building interior and exterior, pictures of floor plans and flat tables listing other information, such as price, terms, special features and broker information. Visualizing this same information in two-dimensional space creates problems when the building population is dense, when multiple properties in the same building are depicted, or when multiple floors are displayed with their respective visual media. Furthermore, information relevant to the real estate acquisition process becomes inaccessible or lost in two-dimensions (e.g., suite views, relative size of the building, and availability of the real estate for sale or lease within the building or the proximity).
A tool known as a Geographical Information System (GIS) has recently become available to the public to show physical locations on a virtual map of the world, and one example of an implementation of this tool is Google® Earth. A map is rendered in two-dimensional form, and geographical objects, such as buildings or infrastructure, may be rendered in a three-dimensional form (within the two dimensions of the viewing screen). A GIS, as a computer-based data-processing application, uses a language for data input, and generally outputs the resulting image to a screen. For example, Google® Earth uses a GeoXML language named Keyhole Markup Language (KML), for expressing geographic annotation and visualization on two-dimensional and three-dimensional maps. Features, such as the shape of the exterior of a building, may be marked on Google® Earth maps by means of KML.
Attempts have been made to show geographical features on a GIS, such as for geographically displaying oil and gas related information. For instance, output files are created based on aggregations of oil and gas data, in particular drilling activity, completion activity, open acreage, well information, well production, land activity, and land boundaries, which output files are able to be overlaid on satellite images in a GIS, and may therefore be visually represented. However, no information is provided regarding the applications in structures above the ground level (e.g., determining the location of and showcasing available space within three-dimensional structures viewable in a GIS in a real estate context).
Hence, there is a need for a means for displaying three-dimensional structural objects in a geographical information system that visually depicts geographically unique information.